From a9e552949606dcd32af9a6cc206f0936d0202a47 Mon Sep 17 00:00:00 2001
From: zhengjun10 <zhengjun10@huawei.com>
Date: Wed, 21 Apr 2021 16:50:35 +0800
Subject: [PATCH] fix activation grad bug

---
 .../runtime/kernel/arm/fp32_grad/activation_grad.cc   |  2 +-
 mindspore/lite/tools/anf_exporter/anf_exporter.cc     | 11 ++++++-----
 2 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/mindspore/lite/src/runtime/kernel/arm/fp32_grad/activation_grad.cc b/mindspore/lite/src/runtime/kernel/arm/fp32_grad/activation_grad.cc
index 2f9dd9b7b6c..5c1ff35886f 100644
--- a/mindspore/lite/src/runtime/kernel/arm/fp32_grad/activation_grad.cc
+++ b/mindspore/lite/src/runtime/kernel/arm/fp32_grad/activation_grad.cc
@@ -66,7 +66,7 @@ int ActivationGradCPUKernel::DoActivation(int task_id) {
       // Sigmoid gets the input tensors in reverse order!
       error_code = SigmoidGrad(input_addr + start, yt_addr + start, count, output_addr + start);
     } else if (param_act_grad_->type_ == schema::ActivationType_TANH) {
-      error_code = TanhGrad(yt_addr + start, input_addr + start, count, output_addr + start);
+      error_code = TanhGrad(input_addr + start, yt_addr + start, count, output_addr + start);
     } else if (param_act_grad_->type_ == schema::ActivationType_HSWISH) {
       error_code = HSwishGrad(yt_addr + start, input_addr + start, count, output_addr + start);
     } else if (param_act_grad_->type_ == schema::ActivationType_HSIGMOID) {
diff --git a/mindspore/lite/tools/anf_exporter/anf_exporter.cc b/mindspore/lite/tools/anf_exporter/anf_exporter.cc
index 4576a286ed7..117ead818f7 100644
--- a/mindspore/lite/tools/anf_exporter/anf_exporter.cc
+++ b/mindspore/lite/tools/anf_exporter/anf_exporter.cc
@@ -854,11 +854,12 @@ int AnfExporter::ProcessValueSequence(const ValueNodePtr &value_node, std::uniqu
     (*schema_tensor)->dims = {static_cast<int32_t>(shape.size())};
     (*schema_tensor)->nodeType = NodeType_ValueNode;
     (*schema_tensor)->data.resize(shape.size() * sizeof(int));
-    ret = memcpy_s((*schema_tensor)->data.data(), shape.size() * sizeof(int32_t), shape.data(),
-                   shape.size() * sizeof(int32_t));
-    if (ret != RET_OK) {
-      MS_LOG(ERROR) << "memcpy_s data into schema_tensor failed.";
-      return RET_ERROR;
+    if (!shape.empty()) {
+      if (EOK != memcpy_s((*schema_tensor)->data.data(), shape.size() * sizeof(int32_t), shape.data(),
+                          shape.size() * sizeof(int32_t))) {
+        MS_LOG(ERROR) << "memcpy_s data into schema_tensor failed.";
+        return RET_MEMORY_FAILED;
+      }
     }
     node_id_map_[value_node->fullname_with_scope()] = meta_graphT->allTensors.size();
     output_cnode->inputIndex.emplace_back(meta_graphT->allTensors.size());